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Land-use/land cover change (LUCC) is an important problem in developing and under-developing countries with regard to global climatic changes and urban morphological distribution. Since the 1900s, urbanization has become an underlying cause of LUCC, and more than 55% of the world’s population resides in cities. The speedy growth, development and expansion of urban centers, rapid inhabitant’s growth, land insufficiency, the necessity for more manufacture, advancement of technologies remain among the several drivers of LUCC around the globe at present. In this study, the urban expansion or sprawl, together with spatial dynamics of Hyderabad, Pakistan over the last four decades were investigated and reviewed, based on remotely sensed Landsat images from 1979 to 2020. In particular, radiometric and atmospheric corrections were applied to these raw images, then the Gaussian-based Radial Basis Function (RBF) kernel was used for training, within the 10-fold support vector machine (SVM) supervised classification framework. After spatial LUCC maps were retrieved, different metrics like Producer’s Accuracy (PA), User’s Accuracy (UA) and KAPPA coefficient (KC) were adopted for spatial accuracy assessment to ensure the reliability of the proposed satellite-based retrieval mechanism. Landsat-derived results showed that there was an increase in the amount of built-up area and a decrease in vegetation and agricultural lands. Built-up area in 1979 only covered 30.69% of the total area, while it has increased and reached 65.04% after four decades. In contrast, continuous reduction of agricultural land, vegetation, waterbody, and barren land was observed. Overall, throughout the four-decade period, the portions of agricultural land, vegetation, waterbody, and barren land have decreased by 13.74%, 46.41%, 49.64% and 85.27%, respectively. These remotely observed changes highlight and symbolize the spatial characteristics of “rural to urban transition” and socioeconomic development within a modernized city, Hyderabad, which open new windows for detecting potential land-use changes and laying down feasible future urban development and planning strategies.
Shaker Ul Din; Hugo Wai Leung Mak. Retrieval of Land-Use/Land Cover Change (LUCC) Maps and Urban Expansion Dynamics of Hyderabad, Pakistan via Landsat Datasets and Support Vector Machine Framework. Remote Sensing 2021, 13, 3337 .
AMA StyleShaker Ul Din, Hugo Wai Leung Mak. Retrieval of Land-Use/Land Cover Change (LUCC) Maps and Urban Expansion Dynamics of Hyderabad, Pakistan via Landsat Datasets and Support Vector Machine Framework. Remote Sensing. 2021; 13 (16):3337.
Chicago/Turabian StyleShaker Ul Din; Hugo Wai Leung Mak. 2021. "Retrieval of Land-Use/Land Cover Change (LUCC) Maps and Urban Expansion Dynamics of Hyderabad, Pakistan via Landsat Datasets and Support Vector Machine Framework." Remote Sensing 13, no. 16: 3337.
Liveability is an indispensable component in future city planning and is practically linked with the health status of individuals and communities. However, there was nor comprehensive and universal district-level framework for assessing liveability due to geospatial and social discrepancies among different countries. In this study, using Hong Kong, a highly dense and international city as an example, the Liveability and Health Index (LHI-HK) consisting of 30 indicators was established, with 21 of them related to education, economy, housing, walkability/transport, environment, and health facilities aspects, while the health conditions of citizens in individual districts were examined by other 9 indicators. Respective scoring allocation was determined by statistical reasoning, and was applied to quantify the connections between liveability and health among the 18 districts of Hong Kong in both 2016 and 2019. Temporal changes of spatial features could be traced by this quantitative framework, and obvious correlations between liveability and health were attained, with R values of 0.496 and 0.518 in 2016 and 2019, and corresponding slopes of 0.80 and 0.88, respectively. Based on the statistical results, it was found that Sai Kung and Kwun Tong are the most and the least liveable district of Hong Kong in 2019. The LHI-HK index was well-validated by renowned AARP liveability index and The California Healthy Places Index (HPI), with R values of 0.90 and 0.70, and the potential uncertainties due to data projection were less than 2.5% for all districts, which implicates its relevancy and appropriateness in conducting similar spatial assessments in international cities. Further, both favorable and unfavorable spatial arrangements of each of the 3 district types in Hong Kong were identified, namely residential, commercial, and industrial districts. This opens new windows in enhancing liveability and health status within communities, with the aim of promoting the sustainability of cities in the long run.
Yan Chi; Hugo Mak. From Comparative and Statistical Assessments of Liveability and Health Conditions of Districts in Hong Kong towards Future City Development. Sustainability 2021, 13, 8781 .
AMA StyleYan Chi, Hugo Mak. From Comparative and Statistical Assessments of Liveability and Health Conditions of Districts in Hong Kong towards Future City Development. Sustainability. 2021; 13 (16):8781.
Chicago/Turabian StyleYan Chi; Hugo Mak. 2021. "From Comparative and Statistical Assessments of Liveability and Health Conditions of Districts in Hong Kong towards Future City Development." Sustainability 13, no. 16: 8781.
Excessive traffic pollutant emissions in high-density cities result in thermal discomfort and are associated with devastating health impacts. In this study, an improved data analytic framework that combines geo-processing techniques, social habits of local citizens like traffic patterns and working schedule and district-wise building morphologies was established to retrieve street-level traffic NOx and PM2.5 emissions in all 18 districts of Hong Kong. The identification of possible human activity regions further visualizes the intersection between emission sources and human mobility. The updated spatial distribution of traffic emission could serve as good indicators for better air quality management, as well as the planning of social infrastructures in the neighborhood environment. Further, geo-processed traffic emission figures can systematically be distributed to respective districts via mathematical means, while the correlations of NOx and mortality within different case studies range from 0.371 to 0.783, while varying from 0.509 to 0.754 for PM2.5, with some assumptions imposed in our study. Outlying districts and good practices of maintaining an environmentally friendly transportation network were also identified and analyzed via statistical means. This newly developed data-driven framework of allocating and quantifying traffic emission could possibly be extended to other dense and heavily polluted cities, with the aim of enhancing health monitoring campaigns and relevant policy implementations.
Hugo Mak; Daisy Ng. Spatial and Socio-Classification of Traffic Pollutant Emissions and Associated Mortality Rates in High-Density Hong Kong via Improved Data Analytic Approaches. International Journal of Environmental Research and Public Health 2021, 18, 6532 .
AMA StyleHugo Mak, Daisy Ng. Spatial and Socio-Classification of Traffic Pollutant Emissions and Associated Mortality Rates in High-Density Hong Kong via Improved Data Analytic Approaches. International Journal of Environmental Research and Public Health. 2021; 18 (12):6532.
Chicago/Turabian StyleHugo Mak; Daisy Ng. 2021. "Spatial and Socio-Classification of Traffic Pollutant Emissions and Associated Mortality Rates in High-Density Hong Kong via Improved Data Analytic Approaches." International Journal of Environmental Research and Public Health 18, no. 12: 6532.
Data Openness is considered as an indispensable component for scientific innovation, community engagement and smart city development. In this study, a Data Openness in Air Quality (DOAQ) framework that consists of 3 tiers with a total of 23 open data principles was established to assess and monitor the status and development of data sharing, release and centralization of air quality information in the top 50 smart cities (Top50SC) around the world. The DOAQ utilizes additive formulas with predefined coefficients to obtain scores in each tier, thus reflecting the relative importance on data availability and visibility of different air quality data. The scores of DOAQ were compared with the smart cities scorings from Eden Strategy Institute and ONG&ONG Pte Ltd. (2018), and other socioeconomic attributes (i.e., social, political and humane) within the current study. Strong correlations (i.e., 0.4−0.6) among these indices implicate that the status of air quality reporting could be a good proxy to gauge the environmental data openness in a city. Lastly, good practices (e.g., apps and air quality forecasts), essential criteria and directions for future smart city development on air quality reporting were summarized, with the aim of laying down practical and efficient guidelines for individual smart city that desires to seek for improvements in air quality data openness.
Hugo Wai Leung Mak; Yun Fat Lam. Comparative assessments and insights of data openness of 50 smart cities in air quality aspects. Sustainable Cities and Society 2021, 69, 102868 .
AMA StyleHugo Wai Leung Mak, Yun Fat Lam. Comparative assessments and insights of data openness of 50 smart cities in air quality aspects. Sustainable Cities and Society. 2021; 69 ():102868.
Chicago/Turabian StyleHugo Wai Leung Mak; Yun Fat Lam. 2021. "Comparative assessments and insights of data openness of 50 smart cities in air quality aspects." Sustainable Cities and Society 69, no. : 102868.
Doppler wind LiDAR (Light Detection And Ranging) makes use of the principle of optical Doppler shift between the reference and backscattered radiations to measure radial velocities at distances up to several kilometers above the ground. Such instruments promise some advantages, including its large scan volume, movability and provision of 3-dimensional wind measurements, as well as its relatively higher temporal and spatial resolution comparing with other measurement devices. In recent decades, Doppler LiDARs developed by scientific institutes and commercial companies have been well adopted in several real-life applications. Doppler LiDARs are installed in about a dozen airports to study aircraft-induced vortices and detect wind shears. In the wind energy industry, the Doppler LiDAR technique provides a promising alternative to in-situ techniques in wind energy assessment, turbine wake analysis and turbine control. Doppler LiDARs have also been applied in meteorological studies, such as observing boundary layers and tracking tropical cyclones. These applications demonstrate the capability of Doppler LiDARs for measuring backscatter coefficients and wind profiles. In addition, Doppler LiDAR measurements show considerable potential for validating and improving numerical models. It is expected that future development of the Doppler LiDAR technique and data processing algorithms will provide accurate measurements with high spatial and temporal resolutions under different environmental conditions.
Zhengliang Liu; Janet F. Barlow; Pak-Wai Chan; Jimmy Chi Hung Fung; Yuguo Li; Chao Ren; Hugo Wai Leung Mak; Edward Ng. A Review of Progress and Applications of Pulsed Doppler Wind LiDARs. Remote Sensing 2019, 11, 2522 .
AMA StyleZhengliang Liu, Janet F. Barlow, Pak-Wai Chan, Jimmy Chi Hung Fung, Yuguo Li, Chao Ren, Hugo Wai Leung Mak, Edward Ng. A Review of Progress and Applications of Pulsed Doppler Wind LiDARs. Remote Sensing. 2019; 11 (21):2522.
Chicago/Turabian StyleZhengliang Liu; Janet F. Barlow; Pak-Wai Chan; Jimmy Chi Hung Fung; Yuguo Li; Chao Ren; Hugo Wai Leung Mak; Edward Ng. 2019. "A Review of Progress and Applications of Pulsed Doppler Wind LiDARs." Remote Sensing 11, no. 21: 2522.
Although most countries have submitted their Nationally Determined Contributions (NDC), there is a lack of understanding what policies are effective in terms of carbon emission reduction under the announced pledges. We use East Asia as a case study to estimate the importance of national environmental policies in terms of reduction in fossil fuel carbon emissions (FFCO2). We show that the flagship policies of China, Japan, South Korea and Mongolia in the 2010s were generally beneficial in terms of slowing down FFCO2 growth rates. When flagship polices were enacted, annual FFCO2 growth rate has either slowed down by 1% (South Korea), 5% (Mongolia), 8% (China) or even resulted in a decline (Japan) comparing to prior periods. We find that the 12th Five-Year Plan (12th FYP) of China had the strongest footprint in FFCO2 emission dynamics across East Asia in 2010s. The recent slowest rate of FFCO2 growth across East Asia (2011–2015) temporally corresponds to the 12th FYP. This regional pattern of FFCO2 dynamics is driven by decrements in annual growth of FFCO2, coal use and cement production of China (all ˜8% per yer decrease) during the 12th FYP. Using compound periodical growth of FFCO2 emissions, we provide two baseline projections of emission distribution in East Asia, by assuming that all policies are enacted (policy-on) or not (policy-off) in the future. The projections show that policies were beneficial since policy-on scenario results in 24%, 80%, 166% less FFCO2 emissions than in policy-off scenario in East Asia by 2020, 2025 and 2030 respectively. This progress is yet insufficient for reaching NDC goals by 2030. Even in policy-on scenario in 2030, East Asian countries would either experience insufficient decline of FFCO2 like Japan (-13% of FFCO2 comparing to pledged -17%) or increase of FFCO2 like South Korea (11%) and Mongolia (4%) comparing to 2010 level. For China, due to lack of economy-independent goals, we were unable to assess NDC target compliance. We demonstrate that China will remain as the major FFCO2 emitter of EA in near future in any projection. For China, the highest emission cluster will remain at the Eastern Provinces with the strongest power generation demand. These provinces would be responsible for 43% and 52% of FFCO2 emissions in East Asia in policy-off and policy-on scenarios. We concluded that the current efforts of national flagship environmental policies are beneficial but not sufficient for reaching ambitious carbon reduction goals like Paris Agreement. This study once again underlined the necessity in the supranational framework that may control the carbon abatement goals in East Asia. Without the supranational framework, achievements in carbon emission reductions are strongly hindered by the socioeconomic environment and the regional (or sectoral) emphasis of carbon reduction activities within a national economy.
Lev D. Labzovskii; Hugo Wai Leung Mak; Samuel Takele Kenea; Jae-Sang Rhee; Azam Lashkari; Shanlan Li; Tae-Young Goo; Young-Suk Oh; Young-Hwa Byun. What can we learn about effectiveness of carbon reduction policies from interannual variability of fossil fuel CO2 emissions in East Asia? Environmental Science & Policy 2019, 96, 132 -140.
AMA StyleLev D. Labzovskii, Hugo Wai Leung Mak, Samuel Takele Kenea, Jae-Sang Rhee, Azam Lashkari, Shanlan Li, Tae-Young Goo, Young-Suk Oh, Young-Hwa Byun. What can we learn about effectiveness of carbon reduction policies from interannual variability of fossil fuel CO2 emissions in East Asia? Environmental Science & Policy. 2019; 96 ():132-140.
Chicago/Turabian StyleLev D. Labzovskii; Hugo Wai Leung Mak; Samuel Takele Kenea; Jae-Sang Rhee; Azam Lashkari; Shanlan Li; Tae-Young Goo; Young-Suk Oh; Young-Hwa Byun. 2019. "What can we learn about effectiveness of carbon reduction policies from interannual variability of fossil fuel CO2 emissions in East Asia?" Environmental Science & Policy 96, no. : 132-140.
Improving air quality and reducing human exposure to unhealthy levels of airborne chemicals are important global missions, particularly in China. Satellite remote sensing offers a powerful tool to examine regional trends in NO2, thus providing a direct measure of key parameters that strongly affect surface air quality. To accurately resolve spatial gradients in NO2 concentration using satellite observations and thus understand local and regional aspects of air quality, a priori input data at sufficiently high spatial and temporal resolution to account for pixel-to-pixel variability in the characteristics of the land and atmosphere are required. In this paper, we adapt the Berkeley High Resolution product (BEHR-HK) and meteorological outputs from the Weather Research and Forecasting (WRF) model to describe column NO2 in southern China. The BEHR approach is particularly useful for places with large spatial variabilities and terrain height differences such as China. There are two major objectives and goals: (1) developing new BEHR-HK v3.0C product for retrieving tropospheric NO2 vertical column density (TVCD) within part of southern China, for four months of 2015, based upon satellite datasets from Ozone Monitoring Instrument (OMI); and (2) evaluating BEHR-HK v3.0C retrieval result through validation, by comparing with MAX-DOAS tropospheric column measurements conducted in Guangzhou. Results show that all BEHR-HK retrieval algorithms (with R-value of 0.9839 for v3.0C) are of higher consistency with MAX-DOAS measurements than OMI-NASA retrieval (with R-value of 0.7644). This opens new windows into research questions that require high spatial resolution, for example retrieving NO2 vertical column and ground pollutant concentration in China and other countries.
Hugo Wai Leung Mak; Joshua L. Laughner; Jimmy Chi Hung Fung; Qindan Zhu; Ronald C. Cohen. Improved Satellite Retrieval of Tropospheric NO2 Column Density via Updating of Air Mass Factor (AMF): Case Study of Southern China. Remote Sensing 2018, 10, 1789 .
AMA StyleHugo Wai Leung Mak, Joshua L. Laughner, Jimmy Chi Hung Fung, Qindan Zhu, Ronald C. Cohen. Improved Satellite Retrieval of Tropospheric NO2 Column Density via Updating of Air Mass Factor (AMF): Case Study of Southern China. Remote Sensing. 2018; 10 (11):1789.
Chicago/Turabian StyleHugo Wai Leung Mak; Joshua L. Laughner; Jimmy Chi Hung Fung; Qindan Zhu; Ronald C. Cohen. 2018. "Improved Satellite Retrieval of Tropospheric NO2 Column Density via Updating of Air Mass Factor (AMF): Case Study of Southern China." Remote Sensing 10, no. 11: 1789.
Improving air quality and reducing human exposure to unhealthy levels of airborne chemicals are important global missions, particularly in China. Satellite remote sensing offers a powerful tool to examine regional trends in NO2, thus providing a direct measure of key parameters that strongly affect surface air quality. To accurately resolve spatial gradients in NO2 concentration using satellite observations and thus understand local and regional aspects of air quality, a priori input data at sufficiently high spatial and temporal resolution to account for pixel-to-pixel variability in the characteristics of the land and atmosphere are required. In this paper, we adapt the Berkeley High Resolution product (BEHR v3.0A, v3.0B and v3.0C) and meteorological outputs from the Weather Research and Forecasting (WRF) model to describe column NO2 in southern China. The BEHR approach is particularly useful for places with large spatial variabilities and terrain height differences such as China. We retrieved tropospheric NO2 vertical column density (TVCD) within part of southern China, for four seasons of 2015, based upon satellite datasets from Ozone Monitoring Instrument (OMI). Retrieval results are validated by comparing with MAX-DOAS tropospheric column measurements conducted in Guangzhou. BEHR retrieval algorithms are more consistent with MAX-DOAS measurements than OMI-NASA retrieval, opening new windows into research questions that require high spatial resolution, for example retrieving NO2 vertical column and ground pollutant concentration in China and other countries.
Hugo Wai Leung Mak; Joshua L. Laughner; Jimmy Chi Hung Fung; Qindan Zhu; Ronald C. Cohen. Improved Satellite Retrieval of Tropospheric NO2 Column Density via Updating of Air Mass Factor (AMF), Part I: Case Study of Southern China. 2018, 1 .
AMA StyleHugo Wai Leung Mak, Joshua L. Laughner, Jimmy Chi Hung Fung, Qindan Zhu, Ronald C. Cohen. Improved Satellite Retrieval of Tropospheric NO2 Column Density via Updating of Air Mass Factor (AMF), Part I: Case Study of Southern China. . 2018; ():1.
Chicago/Turabian StyleHugo Wai Leung Mak; Joshua L. Laughner; Jimmy Chi Hung Fung; Qindan Zhu; Ronald C. Cohen. 2018. "Improved Satellite Retrieval of Tropospheric NO2 Column Density via Updating of Air Mass Factor (AMF), Part I: Case Study of Southern China." , no. : 1.